Breaking changes, sorry. Also remade the SceneTools hierarchy test to
not be that much redundant -- the name- and ID-based overloads can be
tested together.
These don't copy the data but rather reference the original with
different metadata. That caused use-after-free originally (if the input
variable got deleted or overwritten), the previous commit made it
assert (which was the intention there). Now it works properly.
This is important in case the data aren't owned by the instance but
instead referencing something else, for example the importer, a
memory-mapped file or another instance. Will get increasingly
important for zero-copy data import.
Right now the importer/converter APIs are not checked against the
features so using them wrong will assert and make Python die. But there
are at least the enums exposed now so it's possible to prevent the
assert.
They should be named after the plural EnumSet, not the C++ enum. That
was already done for the enums in the primitives library as well as all
shader flags, but not here. They should all also contain a NONE value
for an empty set.
Breaking change, sorry. To avoid similar mistakes in the future, this is
now documented in the API Conventions page.
In both PluginMetadata and AbstractPlugin itself. This makes the
pluginmanager module depend on the utility module (which currently
contains just the Configuration bindings).
It used to take an initializer list, not anymore. Will test this better
once I have to build e.g. AssimpImporter for some other reason -- then I
can use this function to prefer it for loading glTFs and see how that
manages.
They're unpacked to full floats on element access and packed back from
full floats on mutable access, which makes this all very nice and
transparent. Yay Python!
That's it for now, I'll postpone half-float and matrix types for later
when these are actually needed, as it needs extra testing for the
aligned variants too.
To not have to duplicate these for each and every case, enlarging the
surface for potential bugs. Also changing the signatures to number +
identifier, instead of identifier repeated number of times. Means the
compiler won't be able to deduplicate / overlap the literals in the
binary, but is much more maintainable.
For Numpy this causes the slices to be reported as actual typed Numpy
arrays instead of typeless tuples, which is good I guess? Not sure why
that wasn't the case before, or what is the difference, and how it will
behave for sparse types such as aligned matrices.
It was casting in the wrong direction, causing an unbound type to be
returned and also accessing the data totally wrong. Should have tested
this properly in the first place.
Vladimír Vondruš